Integration of monocular cues to improve depth perception

ABSTRACT

One or more monocular cues are extracted from an original image and combined to enhance depth effect. An original image is acquired and segmented into one or more objects. The objects are identified as being either in the foreground or the background, and an object of interest is identified. One or more depth cues are then extracted from the original image, including shading, brightness, blur and occlusion. The depth cues may be in the form of one or more intermediate images having an improved depth effect. The depth cues are then combined or applied to create an image with enhanced depth effect.

BACKGROUND

The present invention relates to image processing, and more particularlyto a novel approach for using monocular cues acquired from a single twodimensional image to improve depth perception.

Traditionally, the ability to perceive depth from two-dimensional imageshas been accomplished by binocular methods. Binocular methods arediscussed in D. Marr and T. Poggio, "Cooperative Computation of StereoDisparity," Science, vol. 194, pp. 283-287 (1976) and S. Barnard and M.Fischler, "Computational Stereo," Computing Surveys, vol. 14, no. 4, pp.553-572 (December, 1982). Binocular depth cues, such as disparity,required multiple images (i.e., a stereo pair of images) and matching ofcorresponding points, which is a computationally complex and error-pronetask. More recently, researchers have developed monocular approaches bycomparing images using differing apertures, as discussed in A. Pentland,"a New Sense For Depth of Field," IEEE Transactions on Pattern Analysisand Machine Intelligence," vol. 9, no. 4 (July, 1987) and G. Surya andM. Subbarao, "Depth From Defocus By Changing Camera Aperture: a SpatialDomain Approach," Proceedings of IEEE Transactions on Pattern Analysisand Machine Intelligence, pp. 61-67 (1993). Monocular depth cues such asblur, have been used to perceive depth. In these approaches, pointmatching was not required, but multiple images were required for depthperception.

Researchers have begun looking at integration of binocular and monocularcues. Several researchers have studied the result of combining cues toperceive depth from two dimensional images. Examples of this type ofwork include N. Gershon, "Visualizing 3D PET Images," IEEE ComputerGraphics and Applications, vol. 11, no. 3, pp. 11-13 (1991), and S.Marapane and M. Trivedi, "An Active Vision System For Depth Extractionusing Multi-Primitive Hierarchical Stereo Analysis and Multiple DepthCues," SPIE, vol. 1956, pp. 250-262 (1993).

Others have studied how these different cues interact to create a deptheffect. In these studies, binocular cues have been considered importantand large contributors to depth perception in two dimensional images.However, as noted above, multiple images are required to extract thesecues. Examples of this type of work include R. Surdick et al., "RelevantCues For the Visual Perception of Depth: Is Where You See It Where ItIs?," Proceedings on the 38th Meeting On Human Factors and ErgonomicsSociety, pp. 1305-1309 (1994), R. Srinivasan et al., "Computing SurfaceInformation From Monocular and Binocular Cues For Vision Applications,"Proceedings of the 27th Conference of Decision and Control, pp.1085-1089 (1988), and S. Das et al., "Dynamic Integration Of Visual CuesFor Position Estimation," SPIE, vol. 1382, pp. 341-352 (1990).

Therefore, a need exists for a method for improving depth perceptionusing only monocular cues acquired from a single image.

SUMMARY OF THE INVENTION

The image processing techniques of the present invention for modifyingan image to enhance depth effect improve upon the prior art by usingonly monocular cues which are extracted from a single image.

The image processing techniques of the present invention involveextracting one or more depth cues from a single two-dimensional image,and then combining these cues to create a three-dimensional effect.

First, an original image is acquired and stored in memory. Next, objectsin the original image are identified and segmented. A segmentation mapcan be generated which identifies each object in the original image.Each object in the original image is then identified as being either inthe foreground or in the background. An object of interest is identified(usually located in the foreground). One or more depth cues are thenextracted from the original image, including shading, brightness, blurand occlusion cues. The depth cues may be in the form of one or moreintermediate images having an improved depth effect.

A shadow can be generated by extracting the shape of the object ofinterest in the foreground and darkening it to grey like a shadow. Anintermediate shadow image is generated by applying the darkened shadowto the background or one or more background objects to create a shadingeffect. An intermediate brightness image can be created by increasingthe relative intensity or brightness of the object of interest. Anintermediate blur image can be generated by blurring the original image,or by blurring all objects other than the object of interest.

One or more of the intermediate images may be combined to generate acombined image. The combined image is then further enhanced by enlargingthe object of interest, thereby further occluding the other objects inthe combined image. Rather than generating intermediate images inparallel, each of the four cues can be extracted and appliedsequentially to the original image, and without generating intermediateimages. It is not necessary to apply all four depth cues to achieve anenhanced depth effect. One or more of the cues can be applied to enhancedepth. A plurality of depth cues should be combined for optimum results.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 illustrates a flow chart for modifying an image using monocularcues to improve depth perception according to an embodiment of thepresent invention.

FIGS. 2A and 2B illustrate a technique for creating a shadow of anobject of interest and casting the shadow onto a background objectaccording to an embodiment of the present invention.

FIG. 3 illustrates a method for increasing or decreasing the size of animage according to an embodiment of the present invention.

FIGS. 4A-4E illustrate the application of blur, shading and brightnessdepth cues according to an embodiment of the present invention toenhance depth perception.

FIGS. 5A-5D illustrate the application of blur and occlusion depth cuesaccording to an embodiment of the present invention to enhance depthperception.

FIG. 6 illustrates a block diagram of an embodiment of a computer systemwhich may be used to implement the present invention.

DETAILED DESCRIPTION

Referring to the Figures in which like numerals indicate like elements,FIG. 1 illustrates a flow chart for modifying an image using monocularcues to improve depth perception according to an embodiment of thepresent invention. Depth cues are used to perceive depth anddimensionality. The present invention involves extracting the depth cuesfrom a single two-dimensional image, and then combining these cues tocreate a three-dimensional effect. In the embodiment illustrated in FIG.1, the depth cues used to improve depth perception are shading,brightness, blur and occlusion. Other depth cues could also be used.

Referring to FIG. 1, in step 110, an image is acquired using a camera ora similar device. This original image is digitized (if not already indigital form) and stored in memory. The image can be a bit-mapped imageof N×N pixels. Each pixel has an associated intensity or brightness fora monochrome image (i.e., grey scale) or an associated color for a colorimage. Each pixel in a monochrome image can be represented, for example,using eight bits, providing 256 intensity values from 0 to 255, with 0being the darkest or lowest intensity and 255 being the brightest orhighest intensity. Although embodiments of the present invention arediscussed in terms of a monochrome image, the present invention isequally applicable to a color image.

In step 120, the original image is segmented into one or more objects.Objects in an image can be segmented using available techniques.

For example, using one technique, separate images of several objects(i.e., a person, a book and a desk) can be separately obtained andstored in memory. A computer can then identify each object in theoriginal image by matching the objects (i.e., matching the shape and/orcolor/intensity of the objects) in each of the separate images to theobjects in the original image.

A second technique for segmenting objects is to segment or group pixelsin close proximity to each other which have the same (or approximatelythe same) intensity or color.

A third technique can be used to segment objects based on detectedmotion. Using this third technique, a plurality of successive frames ofthe same image are taken over a period of time from the same point andstored. The intensity or color of corresponding pixels of each frame arecompared to identify any pixels which have changed (indicating motion).Pixels which have changed and which are in close proximity to each othercan be grouped together as one or more segmented objects.

After the objects have been segmented, a segmentation map is generatedfor each segmented object identifying the location and boundaries ofeach object in the original image. A segmentation map, for example, canbe a binary image in which the object is white (i.e., a pixel value of255), and all else is black. Each of the objects in the original imageare then identified as being either in the foreground or the background.This can be performed manually by inspecting the original image. Also,one or more objects of interest in the original image can be identified.Typically, the object of interest is a person or item in the foregroundof the image.

In step 130, a shadow of the object(s) of interest (or an object in theforeground) is generated from the original image. Shading (i.e., use ofa shadow) improves depth perception because the object casting theshadow appears to be in front of the object on which the shadow has beencast. The shadow can be generated by extracting the shape of the objectof interest in the foreground and darkening it to grey like a shadow.

In step 140, the generated shadow is then applied to background objectsin the original image to create an intermediate shadow image. It is mostbeneficial to use shading to improve depth perception when backgroundobjects are close enough to have a shadow cast on them. As a result, itmay not be effective to use the shading cue when the background objectsare too far away from the foreground object of interest.

In step 150, the brightness or intensity of the foreground object ofinterest in the original image is increased to create an intermediatebrightness image. In the brightness cue, closer objects appear brighterthan more distant ones. Therefore, the present invention exaggerates thebrightness of closer objects by increasing their intensities. Forexample, all pixels of the object(s) of interest may be increased by 20(for pixel intensities ranging from 0 to 255). The brightness cue canalways be used to improve depth perception regardless of the relativelocation of background objects compared to the location of theforeground object of interest. Alternatively, all objects other than theobject of interest can be decreased in intensity to achieve thebrightness effect.

In step 160, one or more objects are blurred to create an intermediateblur image. Blur is a measure of loss of detail in an image. In the blurcue, when an object is in focus, other objects are blurred. The amountof blur depends on the distance from the focused object. In the presentinvention, one or more objects (or portions thereof) are blurred toexaggerate the depth of objects in the image. Blurring can always beused regardless of the relative location of the object of interest.Blurring is the most effective cue in enhancing depth perception.

Different blurring techniques can be used to exaggerate the depth ofobjects in an image. In a first blurring technique, the foregroundobject of interest is removed from the original image. The remainingimage is then blurred. The object of interest is then superimposed onthe remaining image to create the intermediate blur image.Alternatively, it is unnecessary to remove the foreground object ofinterest. The (focused) foreground object of interest can be copied, andthen superimposed over the entire blurred image to achieve the desireddepth effect.

A second blurring technique uses radial blurring of the image. A pointon the original image which is closest to the viewer is selected, suchas the edge of a book or a person's nose. The selected point is notblurred because it is the closest point in the image and should remainin focus. The entire original image is increasingly blurred outwardly orradially from the selected point. The amount of blurring in the imageincreases in proportion to the distance from the selected point.Alternatively, the entire image (other than the selected point or area)can be blurred a fixed amount.

In addition, a blurred image is the response of the camera to a singlepoint source. This response is called the camera point spread function(PSF), h(x,y), which can be approximated as a Gaussian function:##EQU1## a blurred image g(x,y) can be generated by convolving anoriginal focused image f(x,y) with the PSF h(x,y):

    g(x,y)=f(x,y)*h(x,y),

where x and y are indices indicating positions in the image, and σ is aconstant chosen by the user to affect blurring. In a Gaussian function,σ is the variance. In the above equation for h(x,y), σ affects the widthor range of pixels blurred.

In step 170, all three depth-enhanced intermediate images are combined.The intermediate images can be combined additively by adding thecorresponding pixel values from the three intermediate depth-enhancedimages. Each of the cumulative pixel values is then divided by three.Therefore, there is equal contribution from the shading cue, thebrightness cue and the blur cue to generate the combined image.

Alternatively, the cues may be weighted unequally. For example, becauseblur can be the most effective cue, the blur cue can be given moreweight than the other cues. For example, this can be done by multiplyingpixel values of the intermediate blur image by 2, adding the pixelvalues of the intermediate blur image to the other intermediate pixelvalues, and then dividing the cumulative pixel values by 4 to give moreweight to the blur cue. In this example, the blur cue contributes 50%,while, the shading and brightness cues each contribute 25%.

In step 180, the foreground object of interest is increased in size toocclude or block even more of other objects in the combined image.Occlusion indicates that the occluded object is farther away from theoccluding object (the object of interest). An embodiment of the presentinvention generates the occlusion effect by enlarging or increasing thesize of the foreground object of interest to make the foreground objectof interest appear closer. Alternatively, the remaining (background)objects can be decreased in size to provide the same occlusion effect.Although not required, the step 180 (occlusion) should be performedafter combining the other three cues (intermediate depth-enhancedimages) because step 180 changes the geometry of the image.

The method of FIG. 1 illustrates only one embodiment of the presentinvention for improving depth perception of an image using monocularcues extracted from a single image. According to the present invention,other methods using monocular cues similar to FIG. 1 may be employed toimprove depth perception. For example, while the embodiment of FIG. 1uses all four depth cues (shading, brightness, blur and occlusion) toimprove depth perception, any combination of one or more of the depthcues can be used to improve depth perception. These cues can beperformed or applied to the original image in any order. Also, themethod illustrated in FIG. 1 generates three intermediate images inparallel at steps 140, 150 and 160. Alternatively, each depth cue may beapplied to the original image sequentially or serially and withoutgenerating intermediate images.

FIGS. 2A and 2B illustrate an embodiment for creating a shadow of anobject of interest and casting the shadow onto a background object(steps 130 and 140, FIG. 1). Referring to FIGS. 2A and 2B, an object ofinterest (such as a person) 210 is located in the foreground. Theperson's shadow 220 will be positioned in the background at a distanceZ_(move) behind the person 210 to improve depth perception. A lightsource (such as the sun or a lamp) is assumed to exist and shines downat an angle θ with the Z direction (FIG. 2A) and an angle α with the Ydirection (FIG. 2B). Z_(move), α and ∂ can be manually selected based onexperimentation and which most effectively improve depth perception.

Once, the depth of shadow 220 (Z_(move)) and the angles α and θ havebeen selected, trigonometry can be used to determine how much shadow 220will be displaced in the X (height) direction (X_(move)) and how muchthe shadow will be displaced in the Y (width) direction (Y_(move)) fromperson 210 in the image. In other words, the values X_(move) andY_(move) indicate the location of shadow 220 in the image relative tothe location of person 210.

Using trigonometry, X_(move) may be calculated as:

X_(move) =Z_(move) tan θ. Therefore, if a user would like to cast ashadow five feet behind person 210 in an image with the light or sun atθ=10°, then shadow 220 will be:

X_(move) =5 feet (tan 10°)=0.88 feet shorter than person 210.

In order to place the shadow in the image, the X_(move) value in feetmust be transformed to pixels. The pixel displacement of shadow 220 inthe X direction may be calculated as follows:

X_(pixels) =(X_(move)) (No. of pixels/foot)

For example, if there are 100 pixels for every foot in the image, thenshadow 220 will be

X_(pixels) =0.88 feet (100 pixels/foot)=88 pixels lower than person 210in the image.

Similarly, Y_(move) may be calculated as:

Y_(move) =X_(move) /tan α. And the Y displacement of shadow 220 inpixels can similarly be calculated as:

Y_(pixels) =(Y_(move)) (No. of pixels/foot).

The shadow 220 is generated and applied to the image by extracting theshape of person 210, and darkening pixels in the shape of person 210 tocreate shadow 220. The pixels which are darkened to create shadow 220will be located in the image at the calculated shadow position(X_(pixels), Y_(pixels)). For example, the pixels located at thecalculated shadow position can be darkened by 50 pixel values (on ascale of 0-255) to create shadow 220 in the shape of person 210. Thegenerated shadow is placed in the original image at the relative shadowposition (X_(pixels), Y_(pixels)) by darkening pixels at the relativeshadow position to a grey level.

There may exist several objects in the foreground which should cast ashadow onto the background objects. In such case, the combined shape ofthe foreground objects should be used to generate and cast the shadowonto the background.

FIG. 3 illustrates an embodiment for increasing the relative size of theobject of interest to occlude even more of other objects in the combinedimage (step 180, FIG. 1). Referring to FIG. 3, at step 310, a zoomfactor is selected, typically between zero and two. For example a zoomfactor of 0.8 will reduce the image to 80% of its original size, while azoom factor of 1.5 will increase the size of the image to 150% of itsoriginal size. A zoom factor of 1.3, for example, can be used toincrease the size of the foreground object of interest by 30%, therebyto occlude more of the remaining objects in the image. In such case,only the object of interest is increased in size. The enlargedforeground object is then superimposed on the image to obtain theocclusion effect.

A zoom factor of 0.7, for example, can be used to reduce the size of allobjects other than the object of interest. In such case, the image(other than the object of interest) would be reduced (or dezoomed) to70% of its original size. The foreground object of interest (having itsoriginal size) is then superimposed over the reduced image to providethe occlusion effect.

At step 320 of FIG. 3, it is determined whether or not the zoom factoris greater than or equal to one. If the zoom factor is greater than orequal to one, this indicates a zoom operation (increase the size of theobject or image), and flow proceeds to step 330. At step 330, the objectof interest is zoomed or increased in size based on the zoom factor.

If the zoom factor is less than 1, this indicates a dezoom operation onthe image or objects, and flow proceeds to step 340. At step 340, theimage or object is dezoomed.

An image can be zoomed by supersampling the image. Using this technique,each pixel in the original image is duplicated one or more times toincrease the size of the image.

An image can be dezoomed or decreased in size by sub-sampling the image.Using this technique, a plurality of pixels in the image are sampled andreplaced with a single pixel. For example, every third pixel in theoriginal image can be duplicated in the dezoomed image (deleting theother two pixels), or every three pixels can be averaged to obtain asingle pixel value to replace the three pixels.

The following algorithm or code can be used for the zoom/dezoomoperation according to an embodiment of the present invention:

    ______________________________________                                         1  zoom = 1.2; (in this example, zoom is set to 1.2)                          2  for (i=x; i<x+sizex; ++i)                                                  3  {                                                                          4   for (j=y; j<y+sizeY; ++j)                                                 5   {                                                                         6    for (k=0.0; k<zoom; k+=1.0);                                             7     For (L=0.0; L<zoom; L+=1.0); (for horizontal                            8      and vertical space to be zoomed)                                       9     {                                                                      1o      if ((int) segmentMap[i] [j]==255)                                     11       NewImage [(int) (m+k)] [(int) (n+L)]=                                12        OldImage[i] [j];                                                    13     }                                                                      14   n+=zoom; (move to the next horizontal position                           15       in new image; repeat zoom.)                                          16   }                                                                        17    m+=zoom; n=0.0;                                                         18  }  (move to next vertical position in new                                 19     image; repeat zoom).                                                   ______________________________________                                    

The above algorithm provides one embodiment for super-sampling orsub-sampling an object, depending on whether zoom is greater than one(for zoom operation) or less than one (for dezoom). The original or oldimage is of size (sizeX, sizey). An object in the old image which willbe zoomed by 20% (zoom=1.2) in this example is identified by thesegmentation map (segmentMap). The object to be zoomed is white (pixelvalue of 255) in the segmentation map, and all else in the map is black.In lines 10-12 of the above algorithm, if pixel i,j is part of theobject to be zoomed, then pixel i,j is copied to location m+k, n+1 in anew image (newImage). The pixel i,j in the original image (oldImage) iscopied "zoom" times vertically and horizontally in the new image.

FIGS. 4A-4E illustrate the application of blur, shading and brightnessdepth cues to enhance depth perception. FIG. 4A is an original image ofa person, which is the object of interest in the foreground of theimage. FIG. 4B illustrates an intermediate blur image wherein the entireoriginal image is blurred except for the nose region of the person. Thisprovides the appearance that the nose is closer to the viewer than theremaining items in the image, thereby enhancing depth. FIG. 4Cillustrates an intermediate shadow image achieved by casting a shadow inthe shape of the person onto the original image. In this case, theshadow is in the shape of part of the person's outline or profile. FIG.4D illustrates an intermediate brightness image which is achieved byincreasing the intensity or brightness of the person in the originalimage, while decreasing the intensity of the remaining portion of theimage (i.e., the background of the image). FIG. 4E illustrates an imagewith enhanced depth perception based on the depth cues illustrated inFIGS. 4B, 4C and 4D. The image of FIG. 4E is achieved by combining theintermediate images of FIGS. 4B, 4C and 4D.

FIGS. 5A-5D illustrate the application of blur and occlusion depth cuesto enhance depth perception. FIG. 5A is an original image which includesa portion of a book (object of interest) in the foreground and somebackground objects, including a MATLAB box. FIG. 5B illustrates anintermediate blur image in which all objects in the original image havebeen blurred. FIG. 5C illustrates an intermediate occlusion image inwhich only the book in the foreground (object of interest) has beenzoomed or increased in size. FIG. 5D illustrates an image with enhanceddepth perception based on the depth cues illustrated in FIGS. 5B and 5C.The image of FIG. 5D is achieved by combining the intermediate images ofFIGS. 5B and 5C. To combine FIGS. 5B and 5C, only the enlarged or zoomedforeground object is superimposed onto the intermediate blur image ofFIG. 5B, thereby to further occlude the remaining background objects,and provide increased blurring of the background objects.

FIG. 6 illustrates a block diagram of an embodiment of a computer systemwhich may be used to implement the present invention. Computer system600 is a conventional computer system and includes a computer chassis602 housing the internal processing and storage components, including ahard disk drive (HDD) 604 for storing software and other information, acentral processing unit (CPU) 606 coupled to HDD 604, such as a Pentium®processor manufactured by Intel Corporation, for executing software andcontrolling overall operation of computer system 600. An image processor607 is coupled to CPU 606 for processing received images. Computersystem 600 also includes a random access memory (RAM) 608, a read onlymemory (ROM) 610, an analog-to-digital (A/D) converter 612 and adigital-to-analog (D/A) converter 614, which are also coupled to CPU 606and image processor 607. Computer system 600 also includes severaladditional components coupled to CPU 606 and image processor 607including a monitor 616 for displaying video images and otherinformation to the user, a video input device 618, such as a camera, ascanner or like for capturing video images, a speaker 620 for outputtingaudio, a microphone 622 for inputting audio, a keyboard 624 and a mouse626. Computer system 600 also includes a network interface 628 forconnecting computer system 600 to other computers via a computer networklink. The computer network link may include one or more of a variety ofcomputer networks, including the Internet, and Intranet, a local areanetwork (LAN), a wide area network (WAN) or the like. Network interface628 may be any conventional interface, such as an Ethernet card forconnecting to a local area network (LAN), a modem for connecting to theInternet, etc. Some of the components of computer system 600 can becoupled to one another in a conventional manner, such as through one ormore busses, such as a data bus, an address bus and a control bus.

Video input device 618 receives one or more video images. If thereceived images are in analog form, each image is passed through A/Dconverter 612 to generate bitmapped image. The digital bit mapped imageis then stored in HDD 604 for processing. If video input device 618outputs a digital bitmapped image, this image is stored is HDD 604without use of A/D converter 612.

Under control of CPU 606, image processor 607 modifies the receivedimage to enhance depth effect. In one embodiment, image processor 607generates a plurality of depth cues including cues for shading,brightness, blur and occlusion. Each depth cue may be in the form of anintermediate depth enhanced image which is stored in memory. Each of thedepth cues are then combined to create an image having enhanced deptheffect.

The advantage of the present invention is the use of one or moremonocular cues acquired from a single two-dimensional image to enhancedepth effect. For example, a two-dimensional image may be obtained, andone or more monocular cues acquired from the image. A pseudo-3D imagecan then be generated by combining the monocular cues to enhance deptheffect. The result is a two dimensional image with greatly improveddepth perception (i.e., a pseudo 3D image). This pseudo 3D image maythen be transmitted via a computer network to another computer systemfor display.

There exist many applications in which a three dimensional type deptheffect is desirable. It is not practicable, however, in many instancesto provide actual three-dimensional (3D) images due to the high bit rateor bandwidth requirements for transmitting 3D images. Such applicationsinclude real-time video transmission, such as video conferencing over acomputer network, and virtual applications, such as virtual realitygames. Also, the techniques of the present invention are very attractivefor MPEG4 in low bitrate video coding and in video synthesis.

What is claimed is:
 1. A method of using monocular depth cues in asingle two dimensional image to improve depth perception in the image,said method comprising the steps of:obtaining an image, said imagecomprising one or more objects, each of said objects in the image beingeither in the foreground or the background of the image; segmenting saidone or more objects in the image; identifying which of said objects arein the foreground and which of said objects are in the background of theimage; increasing the brightness of one or more said foreground objectsrelative to the brightness of one or more of said background objects inthe image; blurring one or more said background objects in said image,said steps of increasing and blurring operating to improve depthperception of the image; generating a shadow of one or more saidforeground objects in the image; and casting the generated shadow on oneor more said background objects in the image.
 2. A method of usingmonocular depth cues in a single image to improve depth perception inthe image, said method comprising the steps of:obtaining an image, saidimage comprising one or more objects, each of said objects in the imagebeing either in the foreground or the background of the image;segmenting said one or more objects in the image; identifying which ofsaid objects are in the foreground and which of said objects are in thebackground; increasing the brightness of one or more said foregroundobjects relative to the brightness of one or more of said backgroundobjects in the image; generating a shadow of one or more said foregroundobjects in the image; and casting the generated shadow on one or moresaid background objects in the image, said steps of increasing,generating and casting operating to improve depth perception of theimage.
 3. The method of claim 2 and further comprising the step ofincreasing the size of one or more said foreground objects relative tothe size of one or more said background objects in said image.
 4. Amethod of using monocular depth cues in a single image to improve depthperception in the image, said method comprising the steps of:obtainingan image, said image comprising one or more objects, each of saidobjects in the image being either in the foreground or the background ofthe image; segmenting said one or more objects in the image; identifyingwhich of said objects are in the foreground and which of said objectsare in the background; blurring one or more said background objects insaid image; generating a shadow of one or more said foreground objectsin the image;and casting the generated shadow on one or more saidbackground objects in the image, said steps of blurring, generating andcasting operating to improve depth perception of the image.
 5. Themethod of claim 4 and further comprising the step of increasing the sizeof one or more said foreground objects relative to the size of one ormore said background objects in said image.
 6. A method of usingmonocular depth cues in a single image to improve depth perception inthe image, said method comprising the steps of:obtaining an image, saidimage comprising one or more objects, each of said objects in the imagebeing either in the foreground or the background of the image;segmenting said one or more objects in the image; identifying which ofsaid objects are in the foreground and which of said objects are in thebackground; generating a shadow of one or more said foreground objectsin the image; casting the generated shadow on one or more saidbackground objects in the image; and increasing the size of one or moresaid foreground objects relative to the size of one or more saidbackground objects in said image, said steps of generating, casting andincreasing operating to enhance depth perception of the image.
 7. Amethod of using monocular depth cues in a single image to improve depthperception in the image, said method comprising the steps of:obtainingan image, said image comprising one or more objects, each of saidobjects in the image being either in the foreground or the background ofthe image; segmenting said one or more objects in the image; identifyingwhich of said objects are in the foreground and which of said objectsare in the background; increasing the brightness of one or more saidforeground objects relative to the brightness of one or more of saidbackground objects in the image; blurring one or more said backgroundobjects in said image; generating a shadow of one or more saidforeground objects in the image; casting the generated shadow on one ormore said background objects in the image; and increasing the size ofone or more said foreground objects relative to the size of one or moresaid background objects in said image, said steps of increasig thebrightness, blurring, generating, casting and increasing the sizeoperating to enhance depth perception of the image.
 8. The method ofclaim 7 wherein said step of segmenting comprises the step of groupinglike pixels together based on intensity which are in close proximity toone another, each said pixel group comprising a segmented object.
 9. Themethod of claim 7 wherein said step of segmenting comprises the stepsof:obtaining a plurality of successive frames of an image from the samepoint; comparing corresponding pixels in each of the plurality offrames; identifying, based on said step of comparing, any pixels whichhave changed; and grouping together pixels in close proximity which havechanged, each said pixel group comprising a segmented object.
 10. Themethod of claim 7 wherein said step of increasing the brightness of oneor more said foreground objects comprises the step of decreasing thebrightness only of one or more of said background objects in the image.11. The method of claim 7 wherein said step of increasing the brightnessof one or more said foreground objects comprises the step of increasingthe brightness of only one or more said foreground objects.
 12. Themethod of claim 7 wherein said step of blurring comprises the stepsof:removing one or more said foreground objects from the image leaving aremaining image; blurring the objects in the remaining image; andsuperimposing the removed foreground objects onto the blurred remainingimage.
 13. The method of claim 7 wherein said step of blurring comprisesthe step of convolving an original focused image with a point spreadfunction to obtain a blurred image.
 14. The method of claim 7 whereinsaid step of generating a shadow comprises the steps of:calculating thex position of the shadow; and calculating the y position of the shadow.15. The method of claim 14 wherein said step of casting the generatedshadow comprises the step of decreasing the brightness of pixels at thecalculated position of the shadow in the image and in the shape of oneor more of said foreground objects.
 16. The method of claim 7 whereinsaid step of increasing the size of one or more said foreground objectscomprises the steps of:removing one or more said foreground objects fromthe image leaving a remaining image; supersampling the pixels in theremoved foreground objects to generate one or more larger foregroundobjects; and superimposing the one or more larger foreground objectsonto the remaining image.
 17. A method of using monocular depth cues ina single image to improve depth perception in the image, said methodcomprising the steps of:obtaining an original image, said original imagecomprising one or more objects, each of said objects in the image beingeither in the foreground or the background of the image; segmenting saidone or more objects in the image; identifying which of said objects arein the foreground and which of said objects are in the background;creating an intermediate bright image by increasing the brightness ofone or more said foreground objects in the original image relative tothe brightness of one or more of said background objects; creating anintermediate blurred image by selectively blurring one or more saidbackground objects in said original image; creating an intermediateshadow image by performing steps a) and b):a) generating a shadow of oneor more said foreground objects in the original image; and b) castingthe generated shadow on one or more said background objects in theoriginal image; and combining said intermediate bright image, saidintermediate blurred image and said intermediate shadow image into asingle final image having enhanced depth perception.
 18. The method ofclaim 17 and further comprising the step of increasing the size of oneor more said foreground objects relative to the size of one or more saidbackground objects in said final image, thereby causing one or more saidforeground objects to at least partially occlude one or more saidbackground objects.
 19. The method of claim 17 wherein said step ofcombining comprises the step of averaging corresponding pixel valuesfrom the intermediate bright image, the said intermediate blurred imageand the intermediate shadow image to generate a combined image.
 20. Themethod of claim 17 wherein said step of combining comprises the stepsof:adding together corresponding pixel values from the intermediatebright image, the said intermediate blurred image and the intermediateshadow image to generate cumulative pixel values for each pixel in theimage; and dividing each cumulative pixel value by three to generate acombined image.
 21. A method of using monocular depth cues in a singleimage to improve depth perception in the image, said method comprisingthe steps of:obtaining an image, said image comprising one or moreobjects, at least one of said objects being of interest; segmenting saidone or more objects in the image; identifying which of said objects areof interest and the remaining objects not of interest; increasing thebrightness of said one or more objects of interest relative to thebrightness of the remaining objects in the image not of interest;blurring said remaining objects not of interest; generating a shadow ofsaid one or more objects of interest in the image; casting the generatedshadow of the objects of interest onto said one or more remainingobjects in the image not of interest; and increasing the size of saidone or more objects of interest relative to the size of said one or moreremaining objects in said image not of interest, said steps ofincreasing the brightness, blurring, generating, casting and increasingthe size operating to enhance depth perception of the image.
 22. Amethod of using monocular depth cues in a single image to improve depthperception in the image, said method comprising the steps of:obtainingan image, said image comprising one or more objects, each of saidobjects in the image being either in the foreground or the background ofthe image; segmenting said one or more objects in the image; identifyingwhich of said objects are in the foreground and which of said objectsare in the background; to adjust a view of a foreground object relativeto a background object in the image, performing at least two operationsselected from the group consisting of: a) increasing the brightness ofone or more said foreground objects relative to the brightness of one ormore of said background objects in the image; b) blurring one or moresaid background objects in said image; c) generating a shadow of one ormore said foreground objects in the image and casting the generatedshadow on one or more said background objects in the image; and d)increasing the size of one or more said foreground objects relative tothe size of one or more said background objects in said image.